The Experts below are selected from a list of 162 Experts worldwide ranked by ideXlab platform
Ali Zilouchian - One of the best experts on this subject based on the ideXlab platform.
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Authors' Reply [to "Corrections and Comments to 'Model Reduction of Discrete Linear Systems Via Frequency-Domain Balanced Structure'"]
IEEE Transactions on Circuits and Systems I: Regular Papers, 2007Co-Authors: Dali Wang, Ali ZilouchianAbstract:For original paper, see N. L. Prajapathy et al., ibid, vol. 54, no. 3, pp. 682-683, (2007). Reply to the comments on model reduction technique for discrete linear time invariant systems are presented. The proposed technique is based on a conceptual view point of the controllability and Observability Grammians balancing of a system in an arbitrary frequency range. It can be considered as the generalization of the Moore's (1981) balance structure approach in a specific frequency range of operation. Two modified Lyapunov equations are derived for the proposed frequency domain balancing. The transfer function of the sixth-order Cheby-shev type 1 filter is considered. The Nyquist plots for the original filter as well as the reduced-order filters based on the Moore's balanced technique and the proposed method.
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An Algorithm for Balanced Approximation and Model Reduction of 2-D Separable-in-Denominator Filters
Multidimensional Systems and Signal Processing, 2005Co-Authors: Dali Wang, Ali ZilouchianAbstract:Model reduction of two-dimensional (2-D) Separable-in-Denominator Digital Filters (SDDF) using frequency domain balanced realization is proposed. The frequency domain controllability and Observability Grammians are introduced and their appropriate Lyapunov equations are developed. The approach could be viewed as the generalization of the existing balanced structure approach in a specific frequency range of operation. Various properties of the proposed frequency domain balanced structure are investigated. A comparison study of the proposed method with the available techniques is presented using numerical examples
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Identification and approximation of one-dimensional and two-dimensional digital filters
1998Co-Authors: Ali Zilouchian, Dali WangAbstract:In this dissertation, identification and approximation of one-dimensional (1-D) and two-dimensional (2-D) recursive digital filters are addressed. In the identification phase, a novel Neural Network (NN) structure is proposed which provides the state-space model of 1-D filters based upon input-output data. The state space identification technique is also extended to 2-D digital filters and several comparison studies are performed. In the approximation phase, frequency-domain balanced structures for 1-D as well as 2-D digital filters are proposed. The model reduction technique is based on the conceptual view point of balancing the controllability and Observability Grammians of a digital filter in an arbitrary frequency range of operation. Finally, the interrelations between these two phases are presented. Extensive simulation experiments are presented to demonstrate the effectiveness of proposed methods.
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Model reduction of discrete linear systems via frequency domain balanced structure
Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207), 1998Co-Authors: Dali Wang, Ali ZilouchianAbstract:A novel model reduction technique for discrete linear time invariant systems is presented. The proposed technique is based on a conceptual view point of the controllability and Observability Grammians balancing of a system in an arbitrary frequency range. It can be considered as the generalization of the Moore's (1981) balance structure approach in a specific frequency range of operation. Two modified Lyapunov equations are derived for the proposed frequency domain balancing. Various properties of the reduced model such as controllability, Observability, stability, its uniqueness and the error bound are examined. A comparison study of the proposed method with the Moore's time domain technique is presented using a sixth order digital filter.
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Model reduction of two-dimensional separable-in-denominator systems via frequency domain balanced realization
Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 1998Co-Authors: Dali Wang, Ali Zilouchian, R. CarrollAbstract:Model reduction of a class of two-dimensional (2-D) separable-in-denominator digital filters (SDDF) using frequency domain balanced realization is proposed. The frequency domain controllability and Observability Grammians are introduced. Their appropriate Lyapunov equations are developed. Various properties of the proposed frequency domain balanced structure are investigated. A comparison study of the proposed method with the available techniques is presented using a numerical example.
W. Li - One of the best experts on this subject based on the ideXlab platform.
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Algorithms and methodology in physical domain optimization for high-performance vlsi design
2020Co-Authors: D. Zhou, W. LiAbstract:Computer-Aided Design (CAD) tools are extensively used throughout all of the steps in a VLSI design flow. The physical design domain is one of the three domains that are conceptually abstracted in representing a VLSI design flow. This research work focuses on three areas in VLSI physical design domain: clock tree design and buffer insertion, interconnect model order reduction and LVS verification. First, an optimal buffer insertion for clock delay and skew minimization algorithm is developed based on the theory that the minimal clock delay can be obtained by equalizing derivatives of a convex function, and the minimal clock skew can be achieved by equalizing delay functions of different source-to-sink paths. Experimental results show that the presented algorithm achieves both minimal delay and skew in real clock tree design. Further, an automatic clock tree design algorithm is developed for realizing the pre-specified clock arrival time requirements that often occur in an IP block based design environment. In this proposed strategy, planar clock routing and buffer insertion are carried out simultaneously to minimize clock delay and skew, and a full waveform simulation is applied to ensure the signal integrity necessary for high-speed VLSI design. Second, an efficient balanced truncation realization algorithm is presented for interconnect model order reduction. This algorithm shows that there is no need to solve the whole Lyapunov equation for controllability and Observability Grammians before obtaining approximation to their predominant spaces, and a linear order reduction algorithm can be achieved by extending the O(n) Krylov Subspace Oblique Projection method. Finally, a unique LVS methodology is proposed for the verification of a quad-core microprocessor designed with a triple-well 90-nm CMOS technology. Due to the IP reuse, the standard LVS flow is incapable of handling the additional design complexity in verifying the LVS for the chip designed with multiple power domains. This proposed LVS strategy consists of two phases. The first phase involves verifying LVS at the block level as well as the full-chip level. The second phase aims at verifying the integrity of the multi-power-domain power grid. The proposed LVS methodology was successfully verified by real silicon.
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An efficient balanced truncation realization algorithm for interconnect model order reduction
ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196), 2001Co-Authors: D. Zhou, W. LiAbstract:This paper presents an efficient model order reduction method for VLSI interconnect that is based on balanced truncation realization. Our scheme uses both predominant controllability and Observability spaces, and shows that there is no need to solve the whole Lyapunov equation for controllability and Observability Grammians before obtaining approximation to their predominant spaces. The linear order reduction algorithm can be achieved by extending the O(n) Krylov Subspace Oblique Projection method.
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ISCAS (5) - An efficient balanced truncation realization algorithm for interconnect model order reduction
ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196), 2001Co-Authors: D. Zhou, W. LiAbstract:This paper presents an efficient model order reduction method for VLSI interconnect that is based on balanced truncation realization. Our scheme uses both predominant controllability and Observability spaces, and shows that there is no need to solve the whole Lyapunov equation for controllability and Observability Grammians before obtaining approximation to their predominant spaces. The linear order reduction algorithm can be achieved by extending the O(n) Krylov Subspace Oblique Projection method.
Dali Wang - One of the best experts on this subject based on the ideXlab platform.
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Authors' Reply [to "Corrections and Comments to 'Model Reduction of Discrete Linear Systems Via Frequency-Domain Balanced Structure'"]
IEEE Transactions on Circuits and Systems I: Regular Papers, 2007Co-Authors: Dali Wang, Ali ZilouchianAbstract:For original paper, see N. L. Prajapathy et al., ibid, vol. 54, no. 3, pp. 682-683, (2007). Reply to the comments on model reduction technique for discrete linear time invariant systems are presented. The proposed technique is based on a conceptual view point of the controllability and Observability Grammians balancing of a system in an arbitrary frequency range. It can be considered as the generalization of the Moore's (1981) balance structure approach in a specific frequency range of operation. Two modified Lyapunov equations are derived for the proposed frequency domain balancing. The transfer function of the sixth-order Cheby-shev type 1 filter is considered. The Nyquist plots for the original filter as well as the reduced-order filters based on the Moore's balanced technique and the proposed method.
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An Algorithm for Balanced Approximation and Model Reduction of 2-D Separable-in-Denominator Filters
Multidimensional Systems and Signal Processing, 2005Co-Authors: Dali Wang, Ali ZilouchianAbstract:Model reduction of two-dimensional (2-D) Separable-in-Denominator Digital Filters (SDDF) using frequency domain balanced realization is proposed. The frequency domain controllability and Observability Grammians are introduced and their appropriate Lyapunov equations are developed. The approach could be viewed as the generalization of the existing balanced structure approach in a specific frequency range of operation. Various properties of the proposed frequency domain balanced structure are investigated. A comparison study of the proposed method with the available techniques is presented using numerical examples
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Identification and approximation of one-dimensional and two-dimensional digital filters
1998Co-Authors: Ali Zilouchian, Dali WangAbstract:In this dissertation, identification and approximation of one-dimensional (1-D) and two-dimensional (2-D) recursive digital filters are addressed. In the identification phase, a novel Neural Network (NN) structure is proposed which provides the state-space model of 1-D filters based upon input-output data. The state space identification technique is also extended to 2-D digital filters and several comparison studies are performed. In the approximation phase, frequency-domain balanced structures for 1-D as well as 2-D digital filters are proposed. The model reduction technique is based on the conceptual view point of balancing the controllability and Observability Grammians of a digital filter in an arbitrary frequency range of operation. Finally, the interrelations between these two phases are presented. Extensive simulation experiments are presented to demonstrate the effectiveness of proposed methods.
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Model reduction of discrete linear systems via frequency domain balanced structure
Proceedings of the 1998 American Control Conference. ACC (IEEE Cat. No.98CH36207), 1998Co-Authors: Dali Wang, Ali ZilouchianAbstract:A novel model reduction technique for discrete linear time invariant systems is presented. The proposed technique is based on a conceptual view point of the controllability and Observability Grammians balancing of a system in an arbitrary frequency range. It can be considered as the generalization of the Moore's (1981) balance structure approach in a specific frequency range of operation. Two modified Lyapunov equations are derived for the proposed frequency domain balancing. Various properties of the reduced model such as controllability, Observability, stability, its uniqueness and the error bound are examined. A comparison study of the proposed method with the Moore's time domain technique is presented using a sixth order digital filter.
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Model reduction of two-dimensional separable-in-denominator systems via frequency domain balanced realization
Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171), 1998Co-Authors: Dali Wang, Ali Zilouchian, R. CarrollAbstract:Model reduction of a class of two-dimensional (2-D) separable-in-denominator digital filters (SDDF) using frequency domain balanced realization is proposed. The frequency domain controllability and Observability Grammians are introduced. Their appropriate Lyapunov equations are developed. Various properties of the proposed frequency domain balanced structure are investigated. A comparison study of the proposed method with the available techniques is presented using a numerical example.
T Higuchi - One of the best experts on this subject based on the ideXlab platform.
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Balanced realisations and model reduction of periodically time-varying state-space digital filters
IEE Proceedings - Vision Image and Signal Processing, 1996Co-Authors: X. Yang, Masaki Kawamata, T HiguchiAbstract:The authors discuss balanced realisations and model reduction of periodically time-varying (PTV) state-space digital filters. Controllability and Observability Grammians of PTV state-space digital filters are discussed. It is extremely interesting to notice that although PTV state-space digital filters can be implemented by using a group of time-invariant coefficient sets, controllability and Observability Grammians cannot be evaluated independently by using any one set of these time-invariant coefficients. Also, important physical interpretations of controllability and Observability Grammians are considered. Based on these analysis results, balanced realisations of PTV state-space digital filters are defined and a synthesis method for balanced realisations is proposed. As one application of balanced realisations, a reduced-order model of a PTV state-space digital filter can be obtained by taking a subsystem of balanced realisation of the PTV state-space digital filter. Finally, a numerical example is given to illustrate the balanced model reduction procedure.
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Coefficient sensitivity analysis of periodically time-varying state-space digital filters
IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1994Co-Authors: X. Yang, Masaki Kawamata, T HiguchiAbstract:This paper considers an analysis of statistical coefficient sensitivity and frequency coefficient sensitivity of Periodically Time-Varying (PTV) state-space digital filters. A statistical coefficient sensitivity is defined by using a virtual PTV state-space digital filter in which the periodically time-varying coefficients are stochastically varying. In order to analyze frequency coefficient sensitivity, a transfer function, which is called Output Sampling Polyphase (OSP) transfer function, is defined and expressed in terms of the coefficients of PTV state-space digital filters in a closed form. A frequency coefficient sensitivity is defined as an integral measure of the OSP transfer function with respect to the coefficients. It turns out that although the definitions of the two kinds of coefficient sensitivities are extremely different, their expressions are the same and closely related to the controllability and Observability Grammians of PTV state-space digital filters. Also, some considerations for the minimization of the coefficient sensitivity are discussed. Finally, a numerical example is given to verify the analysis above and to show the dependence of the coefficient sensitivity on structure of PTV state-space digital filters.
Andras Varga - One of the best experts on this subject based on the ideXlab platform.
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FREQUENCY-WEIGHTED BALANCING RELATED CONTROLLER REDUCTION
IFAC Proceedings Volumes, 2016Co-Authors: Andras Varga, Brian D. O. AndersonAbstract:The efficient solution of a class of controller approximation problems by using frequency-weighted balancing related model reduction approaches is considered. It is shown that for certain standard performance and stability enforcing frequency-weights, the computation of the frequency-weighted controllability and Observability Grammians can be done by solving reduced order Lyapunov equations regardless the controller itself is stable or unstable. The new approach can be used in conjunction with accuracy enhancing square-root and balancing-free techniques recently developed by the authors for the frequency-weighted balancing related model reduction.
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Coprime factor reduction of H ∞ controllers
2003 European Control Conference (ECC), 2003Co-Authors: Andras VargaAbstract:We consider the efficient solution of the coprime factorization based H ∞ controller approximation problems by using frequency-weighted balancing related model reduction approaches. It is shown that for a class of frequency-weighted performance preserving coprime factor reduction as well as for a relative error coprime factor reduction method, the computation of the frequency-weighted controllability and Observability Grammians can be done by solving Lyapunov equations of the order of the controller. The new approach can be used in conjunction with accuracy enhancing square-root and balancing-free techniques developed for the balancing related coprime factors based model reduction.
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On frequency-weighted coprime factorization based controller reduction
Proceedings of the 2003 American Control Conference 2003., 2003Co-Authors: Andras VargaAbstract:We consider the efficient solution of a class of coprime factorization based controller approximation problems by using frequency-weighted balancing related model reduction approaches. It is shown that for some special stability enforcing frequency-weights, the computation of the frequency-weighted controllability and Observability Grammians can be done by solving reduced order Lyapunov equations. The new approach can be used in conjunction with accuracy enhancing square-root and balancing-free techniques developed for the balancing related coprime factors based model reduction.
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Coprime Factor Reduction of H-infinity Controllers
2003Co-Authors: Andras VargaAbstract:We consider the efficient solution of the coprime factorization based H infinity controller approximation problems by using frequency-weighted balancing related model reduction approaches. It is shown that for a class of frequency-weighted performance preserving coprime factor reduction as well as for a relative error coprime factor reduction method, the computation of the frequency-weighted controllability and Observability Grammians can be done by solving Lyapunov equations of the order of the controller. The new approach can be used in conjunction with accuracy enhancing square-root and balancing-free techniques developed for the balancing related coprime factors based model reduction.
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Coprime factor reduction of H∞ controllers
2003 European Control Conference (ECC), 2003Co-Authors: Andras VargaAbstract:We consider the efficient solution of the coprime factorization based H∞ controller approximation problems by using frequency-weighted balancing related model reduction approaches. It is shown that for a class of frequency-weighted performance preserving coprime factor reduction as well as for a relative error coprime factor reduction method, the computation of the frequency-weighted controllability and Observability Grammians can be done by solving Lyapunov equations of the order of the controller. The new approach can be used in conjunction with accuracy enhancing square-root and balancing-free techniques developed for the balancing related coprime factors based model reduction.
